Simulation of Monty Hall Problem

monty_hall_problem_2.py

# Monty Hall Problem
def monty_hall(
    num_iter: int,
    switch: bool
    ):
    # Data object
    obj = []
    
    for iteration in range(num_iter):
        # Possibilities in doors
        doors = ['Car', 'Zonk', 'Zonk']
        # Random doors
        random.shuffle(doors)
        # Index of doors
        l_doors = list(range(0, 3))
        # Dictionary of doors
        d_doors = dict(zip(l_doors, doors))
        # Participant select the initial door
        index_initial = random.choice(l_doors)
        # Host select the zonk door
        d_zonks = {k:v for k, v in d_doors.items() if (k != index_initial and v == 'Zonk')}
        index_zonk = random.choice(list(d_zonks.keys()))
        
        # Strategy
        if switch:
            d_switch = {k:v for k, v in d_doors.items() if k not in [index_initial, index_zonk]}
            switch_index, final_choice = list(d_switch.items())[0]
            # Win-lose statistics
            if final_choice == 'Car':
                win, lose = 1, 0
            else:
                win, lose = 0, 1
        else:
            # Win-lose statistics
            if d_doors[index_initial] == 'Car':
                win, lose = 1, 0
            else:
                win, lose = 0, 1
            
        # Assign new values into list
        try:
            l_temp = [d for d in obj if d['iter'] == iteration][0]
            obj.append(
                {
                    'iter': iteration + 1,
                    'win': l_temp['win'] + win,
                    'lose': l_temp['lose'] + lose
                }
            )
        except:
            obj.append(
                {
                    'iter': iteration + 1,
                    'win': win,
                    'lose': lose
                }
            )
    
    # Return list of object
    return obj